Healthy Immigrant Children: A Demographic and Geographic Analysis

4. Analyzing the Health and Informal and Formal Supports for Immigrant Children

4.1 The Distribution of Immigrant Children by Size of Urban Area

Category A - Immigrant Children and Category B - Non-Immigrant Children of Immigrant parents are heavily concentrated in Canada's largest urban areas. In contrast, while there is certainly an urban bias to the geographic distribution of Category C - Non-Immigrant Children of Non-Immigrant Parents as well, they are more evenly distributed throughout Canada's urban and rural systems. If cities of 100,000 to 500,000 are included, over 90 percent of Category A -Immigrant Children and Category B - Non-Immigrant Children of Immigrant Parents live in metropolitan or medium size cities and less than 10 percent live in Canada's small towns and rural areas.

Focusing on Category A - Immigrant Children and the region of birth of the PMK, one can see that immigrant children of parents born in Asia and to a slightly lesser extent Europe, are almost exclusively concentrated in Canada's largest and medium-sized cities (Table 5). Using the birthplace of the PMK as the basis for classifying Categories B and C - Non-Immigrant Children, one sees much the same concentration in Canada's largest cities, where Asia is the region of the PMK's birth (Table 6). It is also interesting to note that those among Categories B and C - Non-Immigrant Children whose PMK's birthplace was the United States are distributed throughout the urban and rural system in a pattern almost identical to those of Categories B and C - Non-Immigrant Children whose PMK's birthplace was Canada. Notwithstanding the limitations imposed by the sampling frame, both Category A - Immigrant Children, and Category B - Non-Immigrant Children of Immigrant parents, are 'big city kids.'

In the following sub-sections, as we discuss the health status of immigrant children, their support systems and the factors underlying their health status and support systems, this geographical context must always be kept in mind. It suggests that lack of supply of formal services is not a likely explanation for poor health and lack of social support because there are likely to be more formal services in Canada's metropolitan and medium-sized cities compared to small towns and rural areas. This does not, however, mean that immigrant children and their families do not face demographic, language, ethnic and cultural factors and other socio-economic factors which act as barriers to access to the formal services found in Canada's metropolitan and medium size cities. Geography matters, but not exclusively.

Table 4: Percent of Immigrant and Non-Immigrant Children by Urban or Rural Location
Immigrant Family Class	Size of Urban Area					Rural	Total
Immigrant Family Class	>500K	100-500k	30-100k	15-30k	0-15k	Rural	Total
A. Immigrant Children:
2 parents, both immigrants	82.8	11.1	0.7	1.5	1.6	2.2	100.0
1 single parent, immigrant	84.5	6.1	1.2	2.7	4.2	1.4	100.0
B. Non-Immigrant Children of Immigrant Parents:
2 parents, both immigrants/1 an immigrant or immigrant parent	84.7	8.7	2.6	0.5	1.5	1.9	100.0
1 single parent, immigrant	83.9	8.2	3.8	1.2	0.9	2.0	100.0
C. Non-Immigrant Children of Non-Immigrant Parents:
2 parents or 2 adults	39.6	17.9	7.8	3.5	9.3	21.8	100.0
1 single parent	40.4	20.9	12.9	4.3	9.5	12.0	100.0
B3 collapsed into B1. Source: NLSCY 1994

Table 5: Percent of Immigrant Children by Region of Birth of PMK and Urban or Rural Location
Region of Birth of PMK	Size of Urban Area					Rural	Total
Region of Birth of PMK	>500K	100-500k	30-100k	15-30k	0-15k	Rural	Total
United States	68.5	13.6	0.0	0.0	13.4	4.6	100.0
Europe	86.0	9.3	0.3	2.2	1.1	1.2	100.0
Asia	91.2	6.8	0.4	1.2	0.0	0.4	100.0
Other	81.0	11.6	1.3	2.0	1.3	2.7	100.0
Source: NLSCY 1994

4.2 The Health Status of Immigrant Children

There are competing arguments about the health status of immigrant children. One view is that immigrant children are likely to have poorer health than their non-immigrant counterparts, all other things being equal, because of the conditions in many parts of the world from where Canada draws its immigrants. The counter view is that because screening on health is part of the process for immigration to Canada, and as a result of self-selection among those who chose to come to Canada, all other things being equal, immigrant children are likely to be more healthy than non-immigrant children. There is no doubt considerable variation among immigrant children. For example, we might expect that refugee children have considerably lower health status than children of independent immigrants, but the data do not allow us to make so fine an analysis.

Table 6: Percent of Non-Immigrant Children by Region of Birth of PMK and Urban or Rural Location
Region of Birth of PMK	Size of Urban Area					Rural	Total
Region of Birth of PMK	>500K	100-500k	30-100k	15-30k	0-15k	Rural	Total
Canada	38.2	18.5	8.9	3.7	9.7	21.0	100.0
United States	47.9	17.2	7.9	2.7	3.0	21.3	100.0
Europe	68.9	16.0	4.4	2.0	2.8	5.9	100.0
Asia	89.2	4.6	2.7	0.5	2.4	0.5	100.0
Other	80.0	11.1	2.1	1.3	1.7	3.8	100.0
Source: NLSCY 1994

Based on the Peabody Assessment Tool, we used a derived score on physical and health problems (Variable APACS02) to compare the health of Category A - Immigrant Children with Categories B and C Non-Immigrant Children¹¹. Following a division of age groups used by Cheal et al. (1997), we divide children into those between less than 4 years of age and those between 4 and 11 years of age. Table 7 tells us three important things about immigrant children. First, there do not appear to be meaningful differences in the percentage of Category A -Immigrant Children whose health is rated as less than "very good" compared to the percentage of Categories B and C, Non-Immigrant Children of either Immigrant Parents or Non-Immigrant Parents whose health is rated as less than "very good". Secondly, there appear to be only slight differences between younger and older children. Thirdly, there do appear, however, to be meaningful differences between children whose health is rated as less than very good and those with very good health, depending on whether children live in lone-parent families or with two parents, regardless of whether they are Category A - Immigrant or Categories B and C, Non-Immigrant Children of Immigrant parents or Non-Immigrant Parents. Some caution must be applied to this observation given some of the coefficients of variation are very large.

Table 7: Percent of Immigrant and Non-Immigrant Children with Health Problems
Immigrant Family Class	Age
Immigrant Family Class	0 to 3	4 to 11
A. Immigrant Children:
2 parents, both immigrants	9.9^a	9.9^b
1 single parent, immigrant	*	16.3^b
B. Non-Immigrant Children of Immigrant Parents:
2 parents, both immigrants/1 an immigrant or immigrant parent	13.9	15.1
1 single parent immigrant	4.6^a	20.8^b
C. Non-Immigrant Children of Non-Immigrant Parents:
2 parents or 2 adults	9.3	10.9
1 single parent	14.7	17.4
^a Non-releasable estimates: c.v. > 33.3 ^b Marginal estimates 16.6 < c.v. < 33.3 * < 10 observations in the numerator B3 collapsed into B1. Source: NLSCY 1994

Converting the scale on which health status of children is measured into a binary variable between those in good health (i.e., their rating is very good or better on the derived score) and those in poor health (i.e., their rating is less than very good on the derived scale), 18,796 children have 'very good' health status, and 2,659 have 'poor' health status, from a total NLSCY sample size of 21,455¹². Using logistic regression and the Statistics Canada supplied weights, the Basic Model (Table 8) shows that female children (FEMALE) are 28 percent less likely than male children to have their health rated poor. Children of lone parents (SPAR) are 65 percent more likely than children living in two-parent or two-adult families to have their health rated poor. Living in a metropolitan area (METRO) reduces the likelihood that a child will have his or her health rated poor by 21 percent. The AGE variable is statistically significant, but has only a marginal effect on the increased likelihood of poor health. Although these data do not allow us to explain the patterns, we can speculate that the relatively poorer health of children in lone-parent families is due to poverty and lack of access to services, while the relatively better health of urban children reflects easier access to services.

Keeping in mind the limitations of the Peabody Assessment Tool as a measure of health status, children whom we classified as Category A - Immigrant Children (IMMGRAN) are 24 percent less likely than those in Categories B and C - Non-Immigrant children to have their health rated poor. Where the PMK speaks neither official language (NOENGFR), children are 57 percent less likely to have their health rated poor. Similarly, in the Community Model (Table 8), an area with a ten percent higher proportion of recent immigrants (RECIM) decreases the likelihood of children having their health rated poor by 17 percent. An area with a 10 percent higher proportion of the adult population with less than a high school education (LOWED) increases the likelihood of children having their health rated poor by 10 percent. Median family income by area (MEDINCF) is statistically significant, but has very little impact on the likelihood of children having their health rated poor. The region of origin variables in the Basic Model and the ethnicity variables in the Ethnicity Model present highly contradictory results which we believe are related to the small number of actual observations and we have therefore chosen not to interpret them.

These findings would suggest that immigrant children enjoy better health than Canadian-born children but, again, these findings must be viewed very cautiously. We are not able to determine adequately the extent of variation among immigrant groups from different source areas, or to distinguish among categories of immigrants (such as, for example, refugees and economic migrants). The fact that the most recent immigrants seem to be in better health does not tell us whether this is related to the source areas, and we cannot speculate on whether there is a tendency for health status to lessen with greater time in Canada. The results do, however, support our contention that the health of children is strongly related to the characteristics of the parents, including their family status, their connection to and knowledge of the local community and its services, their levels of education, and their geographic location in relation to public services.

Table 8: Models of Health Status Using Logistic Regression
		The Basic Model			The Ethnicity Model			The Community Model
Variable	DF	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Odds Ratio (10% Change)
*INTERCEPT*	1	-2.0392	0.0001		-1.7654	0.0001		-1.9401	0.0001
AGE	1	0.0198	0.0017	1.020	0.0197	0.0019	1.020	0.0214	0.0008	1.022
FEMALE	1	-0.3234	0.0001	0.724	-0.3311	0.0001	0.718	-0.3181	0.0001	0.727
EUROPE	1	0.0466	0.6362	1.048	0.1037	0.3139	1.109	0.1292	0.1989	1.138
ASIA	1	0.6243	0.0001	1.867	0.7582	0.0001	2.134	0.7790	0.0001	2.179
OTHER	1	0.3399	0.0001	1.405	0.3540	0.0001	1.425	0.4264	0.0001	1.523
NOENGFR	1	-0.8428	0.0027	0.431	-0.7955	0.0049	0.451	-0.9125	0.0013	0.402
IMMGRAN	1	-0.2705	0.0303	0.763	-0.2971	0.0178	0.743	-0.2127	0.0919	0.808
SPAR	1	0.0502	0.0001	1.651	0.4724	0.0001	1.604	0.4491	0.0001	1.567
METRO	1	-0.2328	0.0001	0.792	-0.2258	0.0001	0.798	-0.1068	0.0678	0.899
RURAL	1	0.0470	0.4094	1.048	0.0371	0.5158	1.038	-0.1118	0.0653	0.894
FRENCH	1				0.1142	0.0203	1.121
GERMAN	1				0.0661	0.3282	1.068
ITALIAN	1				-0.6151	0.0001	0.541
CHINESE	1				-0.2327	0.1416	0.792
POLISH	1				0.1138	0.3362	1.121
PORTUG	1				-0.0888	0.6115	0.915
SASIAN	1				-0.6740	0.778	0.935
BLACK	1				0.3147	0.0451	1.370
NAMIND	1				-0.1455	0.0001	0.865
PCT65	1							-0.0036	0.3549	0.996	0.965
TOTIMM	1							-0.0037	0.1871	0.996	0.964
RECIM	1							-0.0183	0.0421	0.982	0.833
LOWED	1							0.0095	0.0024	1.010	1.100
UNI	1							-0.0055	0.0989	0.995	0.947
UNEMP25	1							-0.0000	0.4849	1.000	1.000
GOVTRAN	1							0.0076	0.0514	1.008	1.079
MEDINCF	1							-0.0000	0.0117	1.000	1.000
NEIPROB	1							0.0021	0.0859	1.002	1.021
Sample Size		21455			21455			21455
Source: NLSCY 1994

Table 9: Models of Poorer Recent Health Status Using Logistic Regression
		The Basic Model			The Ethnicity Model			The Community Model
Variable	DF	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Odds Ratio (10% Change)
*INTERCEPT*	1	-1.6916	0.0001		-1.363	0.0001		-1.6543	0.0001
AGE	1	-0.0510	0.0001	0.950	-0.0518	0.0001	0.950	-0.0507	0.0001	0.951
FEMALE	1	-0.1348	0.0009	0.874	-0.1355	0.0008	0.873	-0.1317	0.0012	0.877
EUROPE	1	0.2377	0.0052	1.268	0.2038	0.0233	1.226	0.3282	0.0002	1.388
ASIA	1	-0.0581	0.5983	0.944	0.1443	0.2567	1.155	0.1033	0.3676	1.109
OTHER	1	0.1261	0.1023	1.134	0.2218	0.0066	1.248	0.2350	0.0036	1.265
NOENGFR	1	-0.6520	0.0119	0.521	-0.6683	0.0105	0.513	-0.5929	0.0229	0.553
IMMGRAN	1	-0.5201	0.0001	0.594	-0.5266	0.0001	0.591	-0.4793	0.0005	0.619
SPAR	1	0.2340	0.0001	1.264	0.2316	0.0001	1.261	0.2090	0.0001	1.232
METRO	1	0.1446	0.0412	1.156	0.1489	0.0361	1.161	0.3242	0.0001	1.383
MEDIUM	1	0.1596	0.0437	1.173	0.1619	0.0412	1.176	0.2323	0.0037	1.262
RURAL	1	0.0558	0.4582	1.057	0.0622	0.4091	1.064	-0.0112	0.8839	0.989
FRENCH	1				0.1604	0.0005	1.174
GERMAN	1				0.0972	0.1226	1.102
ITALIAN	1				-0.0213	0.8308	0.979
CHINESE	1				-0.1648	0.3038	0.848
POLISH	1				0.1698	0.1048	1.185
PORTUG	1				0.346	0.0131	1.413
SASIAN	1				-0.6082	0.0387	0.544
BLACK	1				-0.0654	0.6968	0.937
NAMIND	1				-0.1994	0.0001	0.819
PCT65	1							0.0068	0.0624	1.007	1.070
TOTIMM	1							-0.0104	0.0001	0.990	0.901
RECIM	1							-0.0005	0.9536	1.000	0.995
LOWED	1							0.0039	0.2013	1.004	1.040
UNI	1							-0.0054	0.0758	0.995	0.948
UNEMP25	1							-0.0000	0.1783	1.000	1.000
GOVTRAN	1							-0.0015	0.9691	1.000	0.985
MEDINCF	1							-0.0000	0.4205	1.000	1.000
NEIPROB	1							0.0031	0.0055	1.003	1.031
Sample Size		21455			21455			21455
Source: NLSCY 1994

4.3 Recent Health Problems

We also examined whether Category A - Immigrant and Categories B and C - Non-Immigrant Children can be differentiated with respect to poorer recent health¹³. Treating poor recent health as a dichotomous variable, 2,844 children fall into the category of having poor recent health and 18,611 fall into the category of having good recent health out of a total sample size of 21,455. In a series of logistic regression models using Statistics Canada weights, (Table 9) results are consistent with those found for health status in most cases.

In the Basic Model (Table 9), Category A - Immigrant Children (IMMGRAN) are 41 percent less likely to indicate poorer recent health. With the increase in AGE from younger children to older children, the likelihood of having poorer recent health goes down marginally. Being a FEMALE child also reduces the likelihood of having poorer recent health by 13 percent. Children in lone-parent families (SPAR) are over 26 percent more likely than those in two-parent families to indicate poorer recent health. In contrast to the above analysis, living in a metropolitan area (METRO) or a medium sized city (MEDIUM) also increases the likelihood that a child indicates poorer recent health (15 and 17 percent respectively) compared to children living in smaller towns. Again, we have chosen not to interpret the odds ratios based on ethnicity and PMKs' region of origin, because of the small number of observations.

In the Community Model (Table 9), a 10 percent higher proportion of recent immigrants by area (TOTIMM) reduces the likelihood of poorer recent health by 10 percent. While the neighbourhood problems index by area (NEIPROB) measure is statistically significant, the parameter estimates are very small and the consequent odds ratios indicate only marginal increases in the likelihood of poorer recent health for those living in areas with higher scores on this index.

Notwithstanding the limitations of the measures of health status used, the small numbers indicating poor health are similar to those reported in surveys of all Canadian children. The National Population Health Survey, Statistics Canada (1998, p. 3) reports that 89 percent of the population younger than 12 was in excellent or very good health in 1996/97. Taking health status and poorer recent health together, Category A - Immigrant Children fare better than Categories B and C - Non-Immigrant Children. Although the evidence is inconclusive, it also suggests that children whose PMKs come from specific regions of origin and children who identify certain ethnocultural groups have odds ratios indicating in some cases a greater likelihood of poorer health or recent poorer health, and this area needs further study. Female children seem to do better than male children, and children of two-parent families seem to be healthier than children in single-parent families. Somewhat surprisingly, living in a metropolitan area decreases the overall likelihood of poor health, but increases the likelihood of recent poor health. This finding needs to be understood in a context where living in either higher levels of concentration of immigrants, or higher levels of recent immigration, which reduce the likelihood of reporting poor health. While living in large cities may have both positive and negative effects on health, therefore, where one lives in the city may be even more important. As a whole the findings indicate significant diversity in patterns of informal support related to community factors.

4.4 Informal Support for Immigrant Children

On behalf of each household, the PMK was asked to respond to the statement, "If something went wrong, no one would help me" (ASPHQ01A), on a 4-point scale between strongly agree and strongly disagree. Aggregating the agree and strongly agree responses, we created Table 10 -"No Help". For households where the time since immigration is less than five years, lone-parent families with an immigrant child from Category A and lone-parent families where the parent is an immigrant but the child is a non-immigrant from Category B are most likely to indicate that they have no informal support (39.3 percent and 73.6 percent respectively). There is also convergence over time among all three categories of children and between children from lone-parent families compared to children in two-parent or two-adult families. This convergence would suggest that the strongest need for improvement of services, or for changing services to meet specific immigrant needs, is among those most recently immigrated, especially those for whom the difficulties of migration are combined with the difficulties of family separations.

Table 10: "No Help" If Something Went Wrong (Percent)
Immigrant Family Class	Years Since Immigration			Non-Immigrant
Immigrant Family Class	0 to 4	5 to 9	10 +	Non-Immigrant
A. Immigrant Children:
2 parents, both immigrants	4.1	9.6	*
1 single parent, immigrant	39.3	16.9	*
B. Non-Immigrant Children of Immigrant Parents
2 parents, both immigrants	4.7	9.0	9.7
1 single parent immigrant	73.6	12.6	4.5
2 parents, 1 an immigrant or immigrant parent, 1 other adult	*	*	5.0^a
C. Non-immigrant Children of Non-Immigrant Parents:
2 parents or 2 adults				5.1^a
1 single parent				7.7
^a Non-releasable estimates: c.v. > 33.3 * < 10 observations in the numerator Source: NLSCY 1994

Using the same format as above, the PMK was also asked to respond to the statement, "I have family and friends who help me feel safe, secure and happy" (ASPHQ01B). The disagree and strongly disagree responses are aggregated in Table 11 - "Family and Friends", indicating that particularly where the time since immigration is less than five years, lone-parent families where the parent is an immigrant but the child is a non-immigrant in Category B are most likely to indicate they have no informal support (45.1 percent).

The results of the logistic regression analyses using the Statistics Canada weights can be found in Table 12, which treats those who agree or strongly agree as one response and those who disagree or strongly disagree as the opposite response to "No Help". Only 1,096 PMKs responded that they agreed or strongly agreed that they had no one to help them. The remaining 20,359 disagreed or strongly disagreed.

Although a strong majority of parents feel that they have friends and relatives to support them, those who do not represent a basis for concern, especially among those who have immigrated recently and have not yet established support networks. In the Basic Model (Table 12), for Category A - Immigrant Children (IMMIGRAN), the likelihood of PMKs indicating no one to help them increases by almost 46 percent. Among the regional origin variables, ASIA and the OTHER origin of PMK group have statistically significant parameter estimates indicating that PMKs are 42 and 23 percent respectively more likely to agree that they have no one to help them if something goes wrong. Being a lone-parent household (SPAR) increases the likelihood of indicating that there is no one to help by 68 percent, while living in a metropolitan area (METRO) increases the likelihood of indicating that there is no one to help by 47 percent.

Table 11: "No Family or Friends" To Provide Support (Percent)
Immigrant Family Class	Years Since Immigration			Non-Immigrant
Immigrant Family Class	0 to 4	5 to 9	10 +	Non-Immigrant
A. Immigrant Children:
2 parents, both immigrants	8.1	16.0	*
1 single parent, immigrant	9.8	*	*
B. Non-Immigrant Children of Immigrant Parents
2 parents, both immigrants	3.3	15.2	7.1
1 single parent immigrant	45.1	10.9	5.8
2 parents, 1 an immigrant or immigrant parent, 1 other adult	*	*	5.3^a
C. Non-immigrant Children of Non-Immigrant Parents:
2 parents or 2 adults				5.6^a
1 single parent				8.5
^a Non-releasable estimates: c.v. > 33.3 * < 10 observations in the numerator Source: NLSCY 1994

None of the ethnocultural identification variables is statistically significant in the Ethnicity Model (Table 12). This finding does not necessarily mean that there is no relationship between ethnocultural factors and levels of informal support, but only that such a relationship is not discernible using this data set.

In the Community Model (Table 12), factors that increase the likelihood of 'no help' are: areas with higher levels of total immigration (TOTIMM) (7 percent); a higher proportion of the adult population with less than grade 9 education (LOWED) (10 percent); a lower proportion of the population with a university education (UNI) (25 percent), and the proportion of neighbourhood income coming from government transfers (GOVTRAN) (10 percent). With each 10 percent change in the parameter, higher median family income (MEDINCF) has almost no effect, but is statistically significant.

Taking the same approach using logistic regression and the Statistics Canada weights to analyze whether households indicated that they have no family or friends to provide support, 1,089 respondents disagreed or strongly disagreed that they had family or friends to help them while the remainder, 20,366 agreed or strongly agreed with the statement.

The Basic Model in Table 13 shows that households with Category A - Immigrant Children (IMMIGRAN) are almost 56 percent more likely to indicate that they do not have family or friends to provide support. Increased age of the child (AGE) and living in a medium size city (MEDIUM) decrease the likelihood of indicating that children and their families have no family or friends to provide support by 2 and 20 percent respectively. In contrast, PMK identification with the other region of origin (OTHER) increases the likelihood of indicating no family or friends to provide support by 26 percent, being in a lone-parent household (SPAR) increases the likelihood by 45 percent and living in a metropolitan area (METRO) increases the likelihood by 286 percent. These findings indicate substantial lack of support for immigrant families, lone parents and those in the largest cities.

In the Ethnicity Model (Table 13), only PMKs of children who identified their ethnicity as GERMAN or Portuguese (PORTUG) are almost 49 percent and 48 percent respectively less likely to indicate that they have no family or friends to provide support. In contrast, PMKs whose children identified their ethnicity as FRENCH, POLISH, or South Asian (SASIAN) are 51 percent, 53 percent and 241 percent respectively more likely to indicate that they have no family or friends to provide support.

The Community Model (Table 12) provides evidence for both the arguments that areas with large established immigrant populations are likely to provide supportive environments and that areas with large new immigrant populations are likely to be provide less support. A ten percent higher proportion of (TOTIMM) is increased by 10 percent, indicates that PMKs are 18 percent less likely to indicate that they have no family or friends to provide support. When the proportion for recent immigration (RECIM) is increased by 10 percent, the odds ratio indicates that PMKs are 103 percent more likely to indicate that they have no family or friends to provide support. Areas where the population has low educational levels (LOWED) and areas where there are high levels of university educated adults (UNI) are also areas where PMKs are more likely to indicate that they have no family or friends to provide support (29 percent and 10 percent respectively).

Table 12: Models of "No Help" Using Logistic Regression
		The Basic Model			The Ethnicity Model			The Community Model
Variable	DF	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Odds Ratio (10% Change)
*INTERCEPT*	1	-3.1905	0.0001		-3.1631	0.0001		-3.30360	0.0001
AGE	1	0.0057	0.5032	1.006	0.0052	0.5386	1.005	0.01040	0.2262	1.010
FEMALE	1	0.0962	0.0939	1.101	0.0983	0.0875	1.103	0.10240	0.0758	1.108
EUROPE	1	-0.1756	0.1890	0.839	-0.1468	0.2908	0.863	-0.20580	0.1313	0.814
ASIA	1	0.3469	0.0064	1.415	0.3961	0.0074	1.486	0.22440	0.0956	1.252
OTHER	1	0.2103	0.0381	1.234	0.2313	0.0313	1.260	0.11870	0.2667	1.126
NOENGFR	1	-0.2245	0.4217	0.799	-0.1802	0.5225	0.835	-0.45720	0.1091	0.633
IMMGRAN	1	0.3758	0.0049	1.456	0.3984	0.0031	1.489	0.29750	0.0277	1.346
SPAR	1	0.5209	0.0001	1.684	0.5320	0.0001	1.702	0.45330	0.0001	1.574
METRO	1	0.3836	0.0003	1.468	0.3824	0.0003	1.466	0.26080	0.0224	1.298
MEDIUM	1	0.0321	0.7934	1.033	0.0326	0.7907	1.033	0.00977	0.9371	1.010
RURAL	1	0.1178	0.2974	1.126	0.1218	0.2853	1.130	0.05100	0.6608	1.052
FRENCH	1				-0.0468	0.4952	0.954
GERMAN	1				-0.1546	0.1212	0.857
ITALIAN	1				0.1895	0.1675	1.209
CHINESE	1				-0.2635	0.1850	0.768
POLISH	1				-0.2707	0.1336	0.763
PORTUG	1				-0.1968	0.4074	0.821
SASIAN	1				0.1093	0.6822	1.116
BLACK	1				-0.4084	0.0906	0.665
NAMIND	1				0.0039	0.9077	1.004
PCT65	1							-0.00947	0.0713	0.991	0.910
TOTIMM	1							0.00718	0.0300	1.007	1.074
RECIM	1							-0.00153	0.8680	0.998	0.985
LOWED	1							0.00933	0.0300	1.009	1.098
UNI	1							0.02250	0.0001	1.023	1.252
UNEMP25	1							-0.02280	0.6665	0.998	0.796
GOVTRAN	1							0.01760	0.0026	1.018	1.192
MEDINCF	1							-0.00000	0.0001	1.000	1.000
NEIPROB	1							-0.00011	0.9459	1.000	0.999
Sample Size		21455			21455			21455
Source: NLSCY 1994

Table 13: Models of "No Family or Friends" to Provide Support Using Logistic Regression
		The Basic Model			The Ethnicity Model			The Community Model
Variable	DF	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Odds Ratio (10% Change)
*INTERCEPT*	1	-2.6784	0.0001		-2.6237	0.0001		-3.27580	0.0001
AGE	1	-0.0188	0.0225	0.981	-0.0193	0.0196	0.981	-0.01330	0.1108	0.987
FEMALE	1	-0.1034	0.0632	0.902	-0.1022	0.0677	0.903	-0.11310	0.0433	0.893
EUROPE	1	0.0762	0.5130	1.079	0.1602	0.1937	1.174	0.11800	0.3275	1.125
ASIA	1	-0.1814	0.2123	0.834	-0.3000	0.0805	0.741	-0.21580	0.1597	0.806
OTHER	1	0.2322	0.0159	1.261	0.2958	0.0045	1.344	0.23880	0.0197	1.270
NOENGFR	1	-0.2681	0.3455	0.765	-0.2396	0.4055	0.787	-0.29460	0.3095	0.745
IMMGRAN	1	0.4438	0.0006	1.559	0.4221	0.0014	1.525	0.36210	0.0063	1.436
SPAR	1	0.3740	0.0001	1.454	0.3881	0.0001	1.474	0.33130	0.0001	1.393
METRO	1	0.2481	0.0096	1.282	0.2464	0.0104	1.279	0.31560	0.0022	1.371
MEDIUM	1	-0.2265	0.0490	0.797	-0.2084	0.0712	0.812	-0.14890	0.2008	0.862
RURAL	1	-0.1347	0.2018	0.874	-0.1205	0.2552	0.887	-0.25420	0.0183	0.776
FRENCH	1				0.4129	0.0001	1.511
GERMAN	1				-0.6634	0.0001	0.515
ITALIAN	1				-0.1327	0.3643	0.876
CHINESE	1				0.1492	0.4495	1.161
POLISH	1				0.4220	0.0021	1.525
PORTUG	1				-0.6440	0.0162	0.525
SASIAN	1				1.2277	0.0001	3.414
BLACK	1				-0.3239	0.1657	0.723
NAMIND	1				-0.0757	0.0814	0.927
PCT65	1							0.00234	0.6378	1.002	1.024
TOTIMM	1							-0.02030	0.0001	0.980	0.816
RECIM	1							0.07090	0.0001	1.073	2.032
LOWED	1							0.02540	0.0001	1.026	1.289
UNI	1							0.00950	0.0147	1.010	1.100
UNEMP25	1							-0.00005	0.3401	1.000	1.000
GOVTRAN	1							0.00381	0.4692	1.004	1.039
MEDINCF	1							0.00000	0.0218	1.000	1.000
NEIPROB	1							-0.00353	0.0660	0.996	0.965
Sample Size		21455			21455			21455
Source: NLSCY 1994

Table 14: Use of Community Services (Percent)
Immigrant Family Class	Years Since Immigration			Non-Immigrant
Immigrant Family Class	0 to 4	5 to 9	10 +	Non-Immigrant
A. Immigrant Children:
2 parents, both immigrants	10.1^b	5.5^a	*
1 single parent, immigrant	13.4^a	47.0^b	*
B. Non-Immigrant Children of Immigrant Parents
2 parents, both immigrants	11.9^b	12.9^b	5.6^b
1 single parent immigrant	*	55.4	21.8^b
2 parents, 1 an immigrant or immigrant parent, 1 other adult	32.1^b	7.2^a	12.8
C. Non-immigrant Children of Non-Immigrant Parents:
2 parents or 2 adults				11.9
1 single parent				34.3
^a Non-releasable estimates: c.v. > 33.3 ^b Marginal estimates: 16.6 < c.v. < 33.3 * < 10 observations in the numerator Source: NLSCY 1994

Table 15: Use of Health Professionals (Percent)
Immigrant Family Class	Years Since Immigration			Non-Immigrant
Immigrant Family Class	0 to 4	5 to 9	10 +	Non-Immigrant
A. Immigrant Children:
2 parents, both immigrants	16.0^b	13.9^b	*
1 single parent, immigrant	12.8^a	51.6^b	*
B. Non-Immigrant Children of Immigrant Parents
2 parents, both immigrants	17.2^b	12.0^b	16.2
1 single parent immigrant	21.8^a	35.5^b	24.9^b
2 parents, 1 an immigrant or immigrant parent, 1 other adult	*	10.9^a	25.2
C. Non-immigrant Children of Non-Immigrant Parents:
2 parents or 2 adults				23.2
1 single parent				37.3
^a Non-releasable estimates: c.v. > 33.3 ^b Marginal estimates: 16.6 < c.v. < 33.3 * < 10 observations in the numerator Source: NLSCY 1994

Taking the tabular and logistic regression analyses together for both questions, what emerges is a picture of those Category A - families with immigrant children indicating a lack of informal support in the early years after immigration to Canada. Consistently, households with immigrant children, lone-parent families and families in metropolitan areas indicate that it is less likely that they have informal support. It is difficult to discern any trends in the data based on region of origin or ethnicity, and we cannot be sure to what extent the needs of lone-parent immigrant families overlap with those of other Canadian families, but there is a clear indication that informal support networks play a key role in the integration of new immigrants, and that they vary considerably from group to group and from place to place.

Table 16: Use of Religious Services (Percent)
Immigrant Family Class	Years Since Immigration			Non-Immigrant
Immigrant Family Class	0 to 4	5 to 9	10 +	Non-Immigrant
A. Immigrant Children:
2 parents, both immigrants	22.1^b	12.2^b	*
1 single parent, immigrant	13.9^a	35.8^a	*
B. Non-Immigrant Children of Immigrant Parents
2 parents, both immigrants	7.2^a	13.1^b	7.3^b
1 single parent immigrant	*	20.0^b	11.9
2 parents, 1 an immigrant or immigrant parent, 1 other adult	*	12.9^a	14.5
C. Non-immigrant Children of Non-Immigrant Parents:
2 parents or 2 adults				9.7
1 single parent				13.7
^a Non-releasable estimates: c.v. > 33.3 ^b Marginal estimates: 16.6 < c.v. < 33.3 * < 10 observations in the numerator Source: NLSCY 1994

4.5 Formal Support for Immigrant Children

Formal support for children and their families is analyzed through a set of questions which ask whether the respondent received help during the past 12 months from community or social service professionals (ASPHQ02A), health professionals (ASPHQ02B) or religious or spiritual leaders (ASPHQ02C). Although many of the coefficients of variation are too large to be released or are marginal estimates at best, there does appear to be a pattern, expressed in Tables 14 to 16. Among Category A - lone-parent families with immigrant children, the percentage who use community services, health professionals and religious services increases between 0 to 4 years since immigration and 5 to 9 years since immigration. The percentages go from 13.4 percent to 47.0 percent for community services, from 12.8 percent to 51.6 percent for health professionals and 13.9 percent to 35.8 percent for use of religious services respectively. One possible interpretation is that as immigrant parents and children learn more about formal services, their use of them increases. Another interpretation is that the increases reflect the growing problems of lone-parenting over time.

Focusing on community services (Table 17), 3,188 respondents indicated that they had received help from a community or social service professional and the remaining 18,267 indicated negatively. The Basic Model, using logistic regression and the Statistics Canada weights, shows that if the child is an immigrant the likelihood of using community or social services declines by 22 percent (IMMGRAN). The likelihood of using community services also declines marginally with age of the child (AGE). Where the region of birth of the PMK is EUROPE or ASIA, the likelihood of using community services declines by 31 and 30 percent respectively. The likelihood of using community services also declines by 53 percent if the PMK speaks neither official language (NOENGFR) and for children living in metropolitan areas (METRO) and medium size cities (MEDIUM), by 15 and 16 percent respectively. In contrast, being a child from a lone-parent family (SPAR) increases the likelihood of use of community services by 286 percent.

When the ethnic group identifiers are taken into account in the Ethnicity Model (Table 17) using logistic regression and the Statistics Canada weights, the likelihood of using community services increases by almost 18 percent for those children who identify their ethnic origin as FRENCH. For those children who identify their ethnic origins as ITALIAN, CHINESE, Portuguese (PORTUG) or BLACK, the likelihood of using community services declines by 25 percent, 50 percent, 61 percent and 38 percent respectively.

In the Community Model (Table 17) using logistic regression and the Statistics Canada weights, an increase of ten percent in the proportion of immigrants in an area decreases the likelihood of using community and social services by seven percent. A difference of ten percent in the proportion of adults with less than a grade-9 education reduces the likelihood of using community and social services by 14 percent while a difference of ten percent in the proportion of adults with a university education reduces the likelihood of using community and social services by nine percent. An increase of ten percent in income in an area resulting from government transfers increases the likelihood of using community and social services by 14 percent. While the neighbourhood problem index (NEIPROB) is statistically significant and associated with a lower likelihood of using community services, the odds ratio have less than a four percent impact in relative terms.

Taken together the models suggest that use of community services is less likely among Category A - Immigrant children especially where the PMK speaks neither official language. The region of origin for the PMK, the ethnic/cultural origin variables for children, city size effect and many of the community model variables are consistent with the view that immigrant children and new immigrant families are less likely to access community services. While it is possible that this is the result of lesser need, the more likely explanation is that cultural and linguistic barriers prevent greater use of these services (cf. Masi et al., 1993). The one variable that operates in the opposite direction is being the child of a lone-parent regardless of whether the parents are immigrants or non-immigrants. Lone-parent families are much more likely to use community and social services and there can be little doubt that such usage is linked to the many problems that children and their lone parents face on a day-to-day basis.

On the use of health professionals to provide help for personal problems, 5,192 respondents provided a positive response and 16,263 responded negatively. This is one of the few cases where being a Category A - Immigrant Child is not statistically significant at p < 0.05 in the Basic Model (Table 18) when logistic regression and the Statistics Canada weights are applied. Greater likelihood of use of health professionals is, however, strongly linked to being a lone-parent (SPAR) and weakly linked to female children (FEMALE). The odds ratio for the former indicates that lone parents are 95 percent more likely to use health professionals while the odds ratio for female children increases the likelihood of use by 8 percent. The remaining statistically significant variables are linked to a lesser propensity to use health professionals. The PMK coming from one of three regions of origin reduces the likelihood of using health professionals by 14 percent for EUROPE, 30 percent for ASIA and 28 percent for OTHER. Living in a metropolitan area (METRO), medium size city (MEDIUM) or rural area (RURAL) also reduces the likelihood of using health professionals by 21 percent, 13 percent and 11 percent respectively.

In the Ethnicity Model using logistic regression and the Statistic Canada weights (Table 18), children whose ethnic identification is FRENCH or ITALIAN are 20 and 24 percent respectively more likely to use the services of health professionals. In contrast, those children whose ethnic identification is CHINESE or South Asian (SASIA) are 37 and 40 percent respectively less likely to use the services of health professionals.

An increase of ten percent in the proportion of immigrants in an area (TOTIMM) results in a seven percent decrease in the likelihood of using the services of a health professional in the Community Model using logistic regression and the Statistics Canada weights (Table 18). In contrast, a ten percent increase in the proportion of recent immigrants in an area (RECIM) increases the likelihood of using the services of health professionals by 47 percent. Median family income (MEDINCF), unemployment in the population over 25 (UNEMP25) and neighbourhood problems (NEIPBROB) are all statistically significant, but only affect the odds ratios fractionally. While immigrants make lesser use of services in general, therefore, they are more likely to turn to health professionals. Given their higher health status, we think the reasons have more to do with lack of access and with barriers to their participation in other areas.

In comparing and contrasting the use health professionals with the use of community and social services professionals, more respondents indicated that they sought help from health professionals compared to community and social services professionals. This is not so surprising given most families are more likely to identify readily a health professional (especially family physicians or general practitioners) in their neighbourhood or near to where they work and to assume that there will be no costs in seeing a health professional because of provincial health insurance plans¹⁴. Alternatively, there is no way of knowing whether the higher rates of use of professional health services are the result of conflating physical health problems with personal health problems.

In terms of the variables identified in the three models in Table 18, there is a strong similarity with those discussed with respect to the use of community and social service professionals. Lone-parenthood again stands out in understanding the likelihood of increased use of services provided by health professionals. Taken together, the region of origin of the PMK and ethnic group identity imply that children and their families from some groups face barriers to health services.

The final set of logistic regression models using the Statistics Canada weights is summarized in Table 19. In these models, we examined the use of religious services as a formal support mechanism. Only 2,456 respondents indicated that they sought help from a religious or spiritual leader, in contrast to 18,999 who provided a negative response to this question.

In the Basic Model (Table 19), being a Category A - Immigrant Child (IMMIGRAN) increases the likelihood of seeking help from a religious or spiritual leader by 79 percent. Higher AGE of the child and being FEMALE increase the likelihood of seeking help from a religious or spiritual leader by three and ten percent respectively. The OTHER origin group also increases the likelihood of seeking help from a religious or spiritual leader by 52 percent. Lone-parenthood (SPAR) increases the likelihood of seeking help from a religious or spiritual leader by almost 48 percent. In contrast if the PMK speaks neither official language (NOENGFR), there is 71 percent decrease in the likelihood that a religious or spiritual leader provided help and living in a metropolitan area (METRO) decreases the likelihood a religious or spiritual leader provided help by 22 percent.

Respondents whose children's ethnic identification is FRENCH or CHINESE in the Ethnicity Model (Table 19) are 30 and 67 percent respectively less likely to have help from a religious or spiritual leader. On the other hand, respondents whose children ethnic or cultural group identification is GERMAN or BLACK are 72 and 56 percent respectively more likely to have help from a religious or spiritual leader.

In the Community Model (Table 19), a ten percent increase in proportion of immigrants (TOTIMM) increases the likelihood of using a religious or spiritual leader for support by 21 percent. In contrast, a 10 percent increase in the proportion of recent immigrants (RECIM), the size of the population with less than a grade 9 education, or the size of the population with a university education reduce the likelihood of using religious or spiritual leaders for support by 31 percent, 20 percent and 24 percent respectively. The effects of the median family income variable (MEDINCF) and the neighbourhood problem index (NEIPROB) are statistically significant but have only marginal effects on the odds ratios.

While the results in Table 19 are not as compelling as those in Tables 17 and 18, they accord with many of the critical variables already identified. Although fewer respondents indicated that they seek help from religious and spiritual leaders, there are indications that families with immigrant children and families and children where religious attachment might be stronger or better organized, such as in established immigrant areas, are more likely to seek help from a religious or spiritual leader. Without measures of religiosity, however, caution should be taken in attaching too much significance to individual ethnic or cultural groups. Lone parents indicated that they are more likely to seek help. Finally, it is worth noting that there are even barriers to seeking help from religious and spiritual leaders if the PMK speaks neither official language and in areas of recent immigration supporting the view that language and the early years of immigration are critical in accessing all formal services.

Table 17: Models of Use of Community Services Using Logistic Regression
		The Basic Model			The Ethnicity Model			The Community Model
Variable	DF	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Odds Ratio (10% Change)
*INTERCEPT*	1	-1.8038	0.0001		-1.7802	0.0001		-1.57830	0.0001
AGE	1	-0.0138	0.0184	0.986	-0.0147	0.0120	0.985	-0.01380	0.0185	0.986
FEMALE	1	-0.0080	0.8403	0.992	-0.0117	0.7669	0.988	-0.00501	0.8993	0.995
EUROPE	1	-0.3726	0.0002	0.689	-0.2396	0.0217	0.787	-0.31110	0.0024	0.733
ASIA	1	-0.3436	0.0041	0.709	-0.1162	0.3822	0.980	-0.21190	0.0863	0.809
OTHER	1	0.0939	0.2194	1.098	0.2341	0.0040	1.264	0.17270	0.0309	1.189
NOENGFR	1	-0.7639	0.0050	0.466	-0.6657	0.0153	0.514	-0.72070	0.0086	0.486
IMMGRAN	1	-0.2497	0.0490	0.779	-0.2621	0.0404	0.769	-0.22290	0.0808	0.800
SPAR	1	1.3494	0.0001	3.855	1.3542	0.0001	3.874	1.34100	0.0001	3.823
METRO	1	-0.1681	0.0089	0.845	-0.148	0.0217	0.862	0.00487	0.9444	1.005
MEDIUM	1	-0.1806	0.0138	0.835	-0.1694	0.0212	0.844	-0.13800	0.0631	0.871
RURAL	1	-0.8420	0.2151	0.919	-0.0917	0.1773	0.912	-0.07430	0.2832	0.928
FRENCH	1				0.1642	0.0002	1.178
GERMAN	1				0.1174	0.0559	1.125
ITALIAN	1				-0.2873	0.0111	0.750
CHINESE	1				-0.6939	0.0005	0.500
POLISH	1				-0.0508	0.6595	0.950
PORTUG	1				-0.9424	0.0001	0.390
SASIAN	1				0.2089	0.3570	1.232
BLACK	1				-0.4779	0.0040	0.620
NAMIND	1				-0.0361	0.1609	0.965
PCT65	1							0.00067	0.8525	1.001	1.007
TOTIMM	1							-0.00767	0.0032	0.992	0.926
RECIM	1							0.00164	0.8375	1.002	1.017
LOWED	1							-0.01500	0.0001	0.985	0.861
UNI	1							-0.00923	0.0023	0.991	0.912
UNEMP25	1							-0.00001	0.2316	1.000	1.000
GOVTRAN	1							0.01310	0.0007	1.013	1.140
MEDINCF	1							-0.00000	0.2789	1.000	1.000
NEIPROB	1							-0.00315	0.0115	0.997	0.969
Sample Size		21455			21455			21455
Source: NLSCY 1994

Table 18: Models of Use of Health Professionals Using Logistic Regression
		The Basic Model			The Ethnicity Model			The Community Model
Variable	DF	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Odds Ratio (10% Change)
*INTERCEPT*	1	-1.0424	0.0001		-1.0609	0.0001		-1.16070	0.0001
AGE	1	-0.0080	0.0929	0.992	-0.0088	0.0630	0.991	-0.00759	0.1118	0.992
FEMALE	1	0.0723	0.0247	1.075	0.0765	0.0178	1.079	0.06590	0.0412	1.068
EUROPE	1	-0.1463	0.0498	0.864	-0.1116	0.1514	0.894	-0.15970	0.0360	0.852
ASIA	1	-0.3620	0.0001	0.696	-0.0892	0.4063	0.915	-0.42940	0.0001	0.651
OTHER	1	-0.3331	0.0001	0.717	-0.2141	0.0031	0.807	-0.35440	0.0001	0.702
NOENGFR	1	-0.1129	0.5294	0.893	-0.0683	0.7247	0.938	-0.07790	0.6678	0.925
IMMGRAN	1	-0.1840	0.0767	0.832	-0.1505	0.1499	0.860	-0.23210	0.0268	0.793
SPAR	1	0.6687	0.0001	1.952	0.6756	0.0001	1.965	0.69740	0.0001	2.009
METRO	1	-0.2342	0.0001	0.791	-0.229	0.0001	0.795	-0.26820	0.0001	0.765
MEDIUM	1	-0.1343	0.0252	0.874	-0.1263	0.0357	0.881	-0.14140	0.0200	0.868
RURAL	1	-0.1141	0.0406	0.892	-0.1094	0.0501	0.896	-0.10200	0.7340	0.903
FRENCH	1				0.1860	0.0001	1.204
GERMAN	1				0.0822	0.1019	1.086
ITALIAN	1				0.2142	0.0061	1.239
CHINESE	1				-0.4675	0.0014	0.627
POLISH	1				-0.0915	0.3146	0.913
PORTUG	1				-0.0256	0.8453	0.975
SASIAN	1				-0.5062	0.0344	0.603
BLACK	1				-0.2389	0.1029	0.787
NAMIND	1				0.0296	0.1530	0.971
PCT65	1							0.00007	0.9810	1.000	1.001
TOTIMM	1							-0.00738	0.0004	0.993	0.929
RECIM	1							0.03850	0.0001	1.039	1.470
LOWED	1							0.00370	0.1326	1.004	1.038
UNI	1							-0.00000	0.9967	1.000	1.000
UNEMP25	1							-0.00002	0.0335	1.000	1.000
GOVTRAN	1							-0.00542	0.0922	0.995	0.947
MEDINCF	1							0.00000	0.0002	1.000	1.000
NEIPROB	1							-0.00651	0.0001	0.994	0.937
Sample Size		21455			21455			21455
Source: NLSCY 1994

Table 19: Models of Use of Religious Services Using Logistic Regression
		The Basic Model			The Ethnicity Model			The Community Model
Variable	DF	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Parameter Estimate	Pr > Chi-Square	Odds Ratio	Odds Ratio (10% Change)
*INTERCEPT*	1	-2.3421	0.0001		-2.3939	0.0001		-2.03450	0.0001
AGE	1	0.0252	0.0001	1.026	0.0264	0.0001	1.027	0.02330	0.0004	1.024
FEMALE	1	0.1060	0.0168	1.112	0.0988	0.0267	1.104	0.10070	0.0239	1.106
EUROPE	1	-0.1850	0.0874	0.831	-0.2528	0.0240	0.777	-0.30040	0.0061	0.741
ASIA	1	0.0087	0.9433	1.009	0.3310	0.0140	1.392	-0.09520	0.4533	0.909
OTHER	1	0.4192	0.0001	1.521	0.3849	0.0001	1.469	0.32640	0.0001	1.386
NOENGFR	1	-1.2486	0.0004	0.287	-1.1572	0.0011	0.314	-1.23320	0.0005	0.291
IMMGRAN	1	0.5846	0.0001	1.794	0.6102	0.0001	1.841	0.65820	0.0001	1.931
SPAR	1	0.3898	0.0001	1.477	0.3728	0.0001	1.452	0.45450	0.0001	1.575
METRO	1	-0.2512	0.0009	0.778	-0.2549	0.0008	0.775	-0.35670	0.0001	0.700
MEDIUM	1	-0.0784	0.3529	0.925	-0.1026	0.2262	0.902	-0.14340	0.0939	0.866
RURAL	1	0.1178	0.1266	1.125	0.1037	0.1810	1.109	0.24700	0.0018	1.280
FRENCH	1				-0.3517	0.0001	0.703
GERMAN	1				0.5437	0.0001	1.722
ITALIAN	1				0.1272	0.2601	1.136
CHINESE	1				-1.0967	0.0001	0.334
POLISH	1				0.0952	0.4248	1.100
PORTUG	1				-0.1424	0.4453	0.867
SASIAN	1				-0.2639	0.3151	0.768
BLACK	1				0.4431	0.0034	1.557
NAMIND	1				0.0339	0.1682	1.035
PCT65	1							-0.00837	0.0517	0.992	0.920
TOTIMM	1							0.01910	0.0001	1.019	1.210
RECIM	1							-0.03640	0.0001	0.964	0.695
LOWED	1							-0.02190	0.0001	0.978	0.803
UNI	1							-0.02690	0.0001	0.973	0.764
UNEMP25	1							-0.00000	0.4928	1.000	1.000
GOVTRAN	1							-0.00572	0.2294	0.994	0.944
MEDINCF	1							0.00000	0.0053	1.000	1.000
NEIPROB	1							0.00152	0.0039	0.996	1.015
Sample Size		21455			21455			21455
Source: NLSCY 1994

¹¹Readers need to recognise that Variable APACS02 is limited in its application as a measure of relative health status focusing only on 4 and 5 year olds as part of an assessment carried out by a non-medical specialist. At the time that this report was produced, the child health variables which are part of Cycle 2 of the NLSCY were not available for analysis. We do not believe that the general arguments presented in this sub-section would be radically altered using other measures of immigrant and non-immigrant children's health status.
¹²Because of non-response factors, the sample size for a particular question in the NLSCY survey does not always equal the total number of children in the study.
¹³Since the cross-tabulations generated mostly values which were either marginal estimates or non-releasable estimates, they are not reported.
¹⁴This assumption, may in fact, be erroneous depending on the nature of the personal problem and whether the physician can find an applicable billing code under the provincial health plan.